Explore

@karaman.is Oct 4, 2026, 1:53 PM

This week's #TidyTuesday is about hospitals in urban centres, from the EU's JRC. The data has quality problems, so I plotted the counts themselves instead. 95% of the counts are even, which suggests hospitals are counted twice.

Code: github.com/gkaramanis/t...

#RStats #dataviz

Two charts side by side under the title "Two hospitals, or none*", with a subtitle about data from the EU's Joint Research Centre. On the left, a bar chart of urban centres by their number of hospitals, from 1 to 32. Even numbers have much taller bars than odd ones. Two hospitals is the most common count at 1,982 urban centres, followed by four at 1,080, six at 677 and eight at 379. No odd number has more than 26. There is no bar at 1, marked with an arrow and the text "No urban centre has a single hospital". A second label reads "95% of hospital counts are even". On the right, one horizontal bar per region, with thickness showing how many urban centres the region has. Each bar is split into a blue part for urban centres with a hospital count and a grey part for those without. The blue share is smallest in Central and Southern Asia at 30%, then Sub-Saharan Africa at 47% and Eastern and South-Eastern Asia at 52%. It is largest in Europe at 95%.

@mitsuoxv.bsky.social Sep 30, 2026, 11:44 AM

My submission for #TidyTuesday, Week 39 on Health metrics in urban centres worldwide. I explore number of hospitals and pharmacies per capita, and pharmacies per hospital by income group.

Code: github.com/mitsuoxv/tid...

Scatter plot faceted by income group (High income, Upper Middle, Lower Middle, and Low income); x-axis is number of hospitals per capita (log scale), and y-axis is number of pharmacies per capita (log scale).

@dslc.io Sep 29, 2026, 6:20 PM

It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io!
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS

@manishdatt.com Sep 29, 2026, 11:46 AM

CDFs for income-segregated urban population based on proximity to a hospital in 2025.

Notebook: dataviz.manishdatt.com/posts/2695/

#TidyTuesday #dataviz #rstats

Cumulative Distribution Function for income-segregated urban population based on proximity to a hospital in 2025.

@nrennie.bsky.social Sep 29, 2026, 8:11 AM

This week's #TidyTuesday data looks at health metrics in cities across the world 🏥 I created a dot density plot of the population density around hospitals 📊

Thanks to @gabspalomo.bsky.social for curating this week's dataset!

#RStats #DataViz #ggplot2

Four-panel dot density chart comparing the median population living within 1 km of a hospital in 2025 across World Bank income groups. Each dot represents approximately 200 people. Low-income countries have 50,000 people, lower-middle-income countries 53,000, upper-middle-income countries 44,000, and high-income countries 28,000. The chart’s main message is that higher-income countries tend to have lower population density around hospitals.

@jonthegeek.com Sep 28, 2026, 6:48 PM

@dslc.io welcomes you to week 39 of #TidyTuesday! We're exploring Health metrics in urban centres worldwide!

📂 https://tidytues.day/2026/2026-09-29
📰 https://human-settlement.emergency.copernicus.eu/ghs_ucdb_2024.php

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds

TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results!
TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club!

How to Participate
Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data.
Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data.
Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language.
Share your output and the code used to generate it on social media with the #TidyTuesday hashtag.

Exterior of a modern hospital building at dusk, with a brick and glass facade lit from within, a colorful sculpture of a child holding balloons on the wall, young trees and a landscaped walkway in front, and a U.S. flag near the entrance. Photo by Acton Crawford on Unsplash, https://unsplash.com/photos/brown-and-white-concrete-building-near-green-trees-under-blue-sky-during-daytime-8PB_TFEy2XQ

@sponce1.bsky.social Sep 28, 2026, 2:52 PM

📊 #TidyTuesday – 2026 W39 | Health metrics in urban centres worldwide
.
🔗: stevenponce.netlify.app/data_visuali...
.
#rstats | #dataviz | #ggplot2

Faceted scatter plot titled "Income looks like the divide. City density explains most of the gap." Four panels, one per World Bank income group, plot the share of residents within 1 km of a hospital against population density (log scale) for 6,427 urban centers. A large dot marks each group's typical city: 23% within 1 km in high-income countries, 33% in upper-middle, 36% in lower-middle, and 36% in low-income, even though high-income cities have about twice as many hospitals per person as low-income cities. The typical cities sit at rising densities, from about 3,000 people per km² (high income) to about 7,300 (low income), and all four lie close to one dashed curve showing the access–density relationship for all cities. Density strips above each panel show where cities fall on the density axis; cities without hospital data lean denser in low-income countries. Source: GHS Urban Centre Database R2024A, European Commission JRC.

@jonthegeek.com Sep 28, 2026, 11:46 AM

These could make good #TidyTuesday datasets! dslc-io.github.io/tidytuesdayR...

@jonthegeek.com Sep 28, 2026, 11:46 AM

A subset of this could make a good #TidyTuesday dataset! dslc-io.github.io/tidytuesdayR...

(or the whole thing, but we'd need it divided up into separate CSVs, each <= 20MB so GitHub doesn't choke)

@jonthegeek.com Sep 28, 2026, 11:44 AM

This could make a good #TidyTuesday dataset! dslc-io.github.io/tidytuesdayR...

@weare.rladies.org Sep 26, 2026, 3:25 PM

```
One last topic before I wrap things up: challenges as practice. #TidyTuesday, #30DayChartChallenge and #30DayMapChallenge are all examples. They give you a prompt and a reason to make something when nobody is assigning you work. It's the perfect way to try something new. 🧵 #rladies

@rajodm.bsky.social Sep 24, 2026, 6:52 PM

re-up because the previous version was not easy to read (or misleading? check the gh repo)

#TidyTuesday 2026 week 38

Overall, African cities have seen their green space quietly disappear

code: github.com/rajodm/TidyT...

#dataviz #rstats #ggplot2

Histogram showing African cities' green space share falling across four decades (1990–2020); nearly all cities cluster under 5% green space, and by 2020 the median was just 4.12%, the lowest of the four decades.

@mickael.canouil.fr Sep 24, 2026, 2:36 PM

This week's #TidyTuesday, drawn in Typst, looks at green space in cities.

I coloured them the way a satellite sees them (ish), sand where green was lost and green where it grew.

m.canouil.dev/tidytuesday/tidytuesday/2026/09/22/

#Typst #DataViz

@mickael.canouil.fr Sep 24, 2026, 2:35 PM

Last week's #TidyTuesday was the Dead Sea Scrolls.

The scribes had two inks, so scripture is in iron-gall ink and everything else is in red ochre.
I set the title in Frank Ruhl Libre, a font drawn for Hebrew and Latin together.

m.canouil.dev/tidytuesday/tidytuesday/2026/09/15/

#Typst #DataViz